Artificial intelligence will have a transformative impact on our world, and it’s only just the beginning. At Dell Technologies, we’re helping our customers simplify and drive data science and AI initiatives that can deliver valuable insights, automation and intelligence to fuel innovation across their IT landscape — from edge locations to core data center and public clouds.
With more than 48 percent of CIOs deploying AI this year, it is increasingly becoming a strategic priority for organizations across industries, sizes and geographies. Yet, deploying and managing AI workloads can be complex and time intensive, requiring extensive hardware/software integration and testing.
To ease this transition and remove complexity, Dell has developed new solutions to help data scientists and developers get their AI applications and projects up and running without delay. Our latest solutions, all globally available today, to help prepare IT environments for AI include:
Dell Cloud-Native Machine Learning with One Convergence® DKube™
One Convergence DKube deep-learning-as-a-service software installation delivers the ease of cloud-like use on-premises to reduce cost by abstracting the underlying accelerated compute and storage. This helps remove operational headaches often encountered with deploying the infrastructure on-premises, especially for key tasks such as model development, training and deployment. This desktop-to-datacenter AI system – which can run on both workstations and servers – automatically recognizes resources for use and can be scaled out by adding nodes to the cluster.
Dell EMC HPC Ready Architecture for AI and Data Analytics
The new Dell EMC HPC Ready Architecture for AI and Data Analytics delivers the power of accelerated AI computing to the edge with an easy-to-deploy cloud native stack. This combination of the Bright Computing® Solution for Edge, the Dell EMC Data Science Portal, PowerEdge servers with NVIDIA GPUs and Isilon scale-out NAS storage enables faster access to data gathered at any location. It also reduces IT silos and consolidates operations for up to three times lower total cost of ownership (TCO) versus running AI, data analytics and HPC workloads on different systems.
Dell EMC Ready Solutions for Data Analytics
Dell EMC Ready Solutions for Data Analytics introduced two new validated architectures today to help customers use AI and data analytics to quickly gain insights from their data through a choice of pre-tested software and hardware configurations based on different use cases.
Dell EMC Ready Solutions for Data Analytics – Spark on Kubernetes
Customers can now speed up large-scale batch and streaming data processing with Apache® Spark™. Built on the successes of Hadoop, Apache Spark is a unified analytics engine that performs data processing in-memory instead of on disk allowing workloads to run 100 times faster.
Dell EMC Ready Solutions for Data Analytics – Splunk Enterprise
Customers now can have the power of Splunk® Enterprise to get real-time insights and business value from machine data, one of the most underused organizational assets. Based on Dell EMC PowerEdge servers, the architecture provides high performance and low latency I/O.
Dell Precision Data Science Workstation Guided Install Edition
Preparation and model training are often the most time-consuming portions of a data scientist’s role. Dell recognizes this and designed the Dell Precision Data Science Workstation portfolio to help data scientists focus on experimenting, exploring and uncovering insight, rather than maintaining AI systems and waiting for model training iterations to complete.
Customers can maximize productivity, speed up processes, yield better quality insights, and lower the cost of projects by running models on a preconfigured, pre-validated Data Science Workstation. Data scientists no longer need to choose between enterprise-class AI platforms or AI platform flexibility.
Based on Dell’s Precision 7000 Series mobile workstations and the 5820 and 7920 tower workstations, the portfolio features NVIDIA® Quadro RTX™ 5000, RTX 6000 and RTX 8000 GPUs. The systems are certified NVIDIA NGC-Ready to help data scientists, developers and researchers quickly deploy AI frameworks with containers and get a head start with pre-trained models or model training scripts. In addition, the Data Science Workstation portfolio is optimized for NVIDIA Data Science Software powered by RAPIDS™, including GPU-optimized XGBoost, TensorFlow, PyTorch and other leading applications.
Dell Precision Data Science Workstation and Dell EMC Isilon scale-out NAS H400 solution for data scientists
AI initiatives generally start small with a data science problem and a proof of concept. This new data science and modeling offering takes advantage of the combined power of the Dell Precision 7920 Tower Data Science Workstation and Dell EMC Isilon scale-out NAS. With this solution, data scientists can build their models on workstations while training these models using data residing on fast, high-performance scale-out shared storage. They can then move to production seamlessly without switching systems or migrating data. With this approach, data scientists won’t need to bring in the data sets locally for training, further increasing productivity and reducing model training time.
Dell EMC Isilon scale-out NAS for Deep Learning Workloads
Dell and NVIDIA have teamed to show how to accelerate and scale deep learning training workloads using the combination of Dell EMC Isilon, Dell EMC PowerSwitch and NVIDIA DGX-2™ systems with NVIDIA V100 Tensor Core GPUs. Following this reference architecture, businesses can deploy faster, achieve greater model accuracy and accelerate business value with AI at scale. Dell EMC Isilon scale-out NAS is also available in an engineering-validated reference architecture design with NVIDIA DGX-1™ systems, simplifying and accelerating the deployment of enterprise-grade AI initiatives.
Regardless of where, or how, your organization employs AI as part of its digital transformation journey, Dell Technologies can help create an AI-ready technology environment. Click here to find out more.